Real-World Performance of Deep-Learning-based Automated Detection System for Intracranial Hemorrhage (CMIMI 2018 Presentation)

Sehyo Yune (MD, MPH, MBA) gave a presentation on her paper “Real-World Performance of Deep-Learning-based Automated Detection System for Intracranial Hemorrhage” at 2018 SIIM Conference on Machine Intelligence in Medical Imaging (CMIMI).

Yune, S., Lee, H., Pomerantz, S., Romero, J., Kamalian, S., Gonzalez, R., Lev, M., Do, S., 2018. Real-World Performance of Deep-Learning-based Automated Detection System for Intracranial Hemorrhage.

Most of currently published deep learning studies in medical image analysis report their performance using carefully selected data. To use such tools in the clinical practice, however, it is critical to know how they work with the real-world data. Here, we evaluated the applicability of our ICH detection system in the clinical setting by comparing the model performance on the real-world cases to the performance on the selected dataset.